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Collibra vs Alation for Data Governance : r/dataengineering
I liked Alation alot. Again, highly competent, slightly less feature rich than Collibra, but way easier to understand. Atlan is much more recent ...
Collibra Data Governance automates workflows and centralizes policies to create a single source of truth. Connect your data ecosystem, improve data discovery and deliver trusted data for analytics and AI.
Products
AI Command CenterCollibra AI Command Center helps enterprises manage and control every AI agent and system across the full AI lifecycle — delivering near real-time visibility, trust signals and built-in compliance, so teams can scale AI safely with measurable impact.
Data GovernanceCollibra Data Governance automates workflows and centralizes policies to create a single source of truth. Operationalize your strategy, ensure regulatory readiness and unlock data value for business initiatives.
Collibra PlatformGovern data and AI with the Collibra Platform. Connect your data ecosystem, improve data discovery and deliver trusted data for analytics and AI.
Data CatalogCreate a complete, centralized inventory of your organization’s data, gain visibility across sources and accelerate data product creation with automated curation and enrichment.
Data Quality & ObservabilityCollibra Data Quality & Observability maintains trustworthy data across your ecosystem, providing detailed profiling and deploying automated and custom monitors to instantly detect and address anomalies.
Data LineageCollibra Data Lineage maps the exact journey of your data, exposing every transformation and dependency. Gain absolute clarity and control across your entire data and AI ecosystem with native, end-to-end visualization.
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Customer feedback
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Collibra Reviews 2026: Details, Pricing, & Features
Users consistently praise Collibra for its robust data governance and user-friendly interface, which facilitate effective data management and collaboration ...
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Collibra Platform vs. Adaptive from Workday
Compare Collibra Platform vs Adaptive from Workday. 403 verified user reviews and ratings of features, pros, cons, pricing, support and more.
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Collibra AI Command Center Customer Reviews 2026 - Infotech
Explore Collibra AI Command Center - AI Governance, Risk, & Compliance reviews from real users. Learn more about product features, ...
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Marketing & Ads
GoogleCollibra Inc.
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LinkedInCollibra
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Speed ships agents. Control scales them.
Join AIUC + Collibra to learn how to supervise agents at scale and act fast when they cross the line.
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GoogleCollibra Inc.
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AI is widening the data chasm. Unify governance to accelerate every data & AI use case.
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GoogleCollibra Inc.
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LinkedInCollibra
Original ad ↗Speed ships agents. Control scales them.
Join AIUC + Collibra to learn how to supervise agents at scale and act fast when they cross the line.
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GoogleCollibra Inc.
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AI is widening the data chasm. Unify governance to accelerate every data & AI use case.
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GoogleCollibra Inc.
Original ad ↗Data Privacy Solutions
AI is widening the data chasm. Unify governance to accelerate every data & AI use case.
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GoogleCollibra Inc.
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LinkedInCollibra
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Your agents are scaling. Is your control?
Learn how to scale agentic AI without losing the wheel. Live Nov. 4 with AIUC + Collibra. Save your seat.
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LinkedInCollibra
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Your agents are scaling. Is your control?
Learn how to scale agentic AI without losing the wheel. Live Nov. 4 with AIUC + Collibra. Save your seat.
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Govern data and AI. All in one place
Visibility, context, and control — from input through output. Learn more.
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GoogleCollibra Inc.
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Take command of data and AI
Real-time Trust Scores and automated traceability for every AI system you run
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Original ad ↗Take command of data and AI
Real-time Trust Scores and automated traceability for every AI system you run
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Request a Collibra Platform demo | Collibra ↗
Speak one-on-one with a Collibra expert and get a personalized demo of the Collibra Data Intelligence Platform.
Observed Nov 11, 2026
New pages
Collibra MCP now on Snowflake Marketplace: How to set it up and put it to work in Snowflake CoWork and CoCo ↗
Collibra Control Tower is here. Your data policies just got a schedule. ↗
Bring SAP S/4HANA metadata into Collibra Platform ↗
Bring your own continuous deployment: Run Collibra Edge upgrades your way ↗
Bring your own model (BYOM): Collibra's AI, plus your model ↗
Delivering operational trust for AI agents ↗
Collibra + Trail ML: Bringing AI governance and automation together ↗
Context is the new IP: Collibra is where enterprises come to protect it ↗
Evolving from data governance to AI decision governance ↗
Are you trusting your AI today? ↗
Data governance for AI: The key life science and biotech prescription ↗
Your AI governance program was built for models that answer. Your agents act. ↗
Collibra achieves AIUC-1 certification: Holding ourselves to the standard we ask of others ↗
Collibra acquires trail ML to automate AI governance from policy to production ↗
Collibra Launches New Capabilities to Reduce the Hallucination Tax on Enterprise AI ↗
Agent Contracts: Set the boundaries for your entire AI agent fleet ↗
Guardian Agents: Keep AI agents in control at runtime ↗
Introducing Collibra Maestro: Automate governance operations, turning days of manual work into minutes ↗
Contextual gravity: Why enterprise AI will standardize on the layer that can't be replicated ↗
When past stops predicting future: why insurance risk modeling needs a new data and AI foundation ↗
Activate metadata through expanded outbound integrations ↗
Escaping CPG’s small package: Privacy, personalization and data reckoning ↗
Data Product Agent: Turn a cataloged table into a governed data product ↗
Context vs control: Why you need both ↗
Your business knows what good data looks like. Who keeps it in check? ↗
Governed AI at the speed of Snowflake: How Collibra MCP powers Snowflake CoWork & Cortex CoCo ↗
Your AI policy exists. Does anything check it? ↗
Data Lineage Read APIs + MCP Server: Lineage on-demand ↗
Data Products application: Centralized oversight for all your Data Products ↗
The readiness gap: Banking's AI ambition outruns persistent capability ↗
Grounding agentic AI with the Collibra MCP for Databricks ↗
Data sharing agreements vs. Data contracts: Two different promises around data ↗
Customer zero: How Collibra built an org-wide AI analyst on its own governed context ↗
Automated AI traceability for Snowflake Cortex ↗
A single governed source of truth for every AI agent and platform: Introducing Collibra’s governed context compiler ↗
Data Product interoperability: Native Integration for Databricks, Google, SAP and Snowflake ↗
Insurance's GenAI unstructured data challenge ↗
SAP Signavio + Collibra: Where process meets governance ↗
The context AI needs. The control you require. ↗
Why AI agents fail: they don't understand your business ↗
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Clock is ticking: Why banks can't ignore unstructured data ↗
AI audit readiness: A checklist for models, agents, and your first AI audit ↗
AI lifecycle governance: Governing models and agents from ideation to decommissioning ↗
AI lineage tracking: From source data to model and agent decision ↗
The AI Trust Layer: Command-Center Architecture for Enterprise-Grade Models and Agents ↗
Agentic AI Governance: A Control-Plane Framework for Governing Autonomous AI Agents at Runtime ↗
AI assurance platforms: Definition, capabilities, and how they manage AI risk ↗
AI Metadata Management: The Context Layer That Makes Models and Agents Trustworthy ↗
AI model and agent monitoring: Metrics, drift detection, and runtime alerting in production ↗
The semantic layer for AI: Why LLMs and agents need business context to be trustworthy ↗
AI Model and Agent Inventory: How to Catalog Every AI System in Your Enterprise ↗
AI regulatory compliance in 2026: EU AI Act, US orders, and state laws, and how to operationalize them ↗
Attribute-Based Access Controls: Right data, right users ↗
Control Tower: OOTB controls to govern AI by exception ↗
Data lineage for AI: Tracing training data, RAG sources, and agent inputs ↗
Govern every AI agent across its full lifecycle ↗
Govern your Microsoft Fabric estate with Collibra ↗
Operationalize the AIUC-1 standard with the new out-of-the-box assessment template ↗
Take control of your Collibra homepage experience ↗
Turn AI activity into measurable business oversight ↗
AI Observability Explained: How to Monitor Models and Agents in Production From One Command Center ↗
The AI risk management framework: NIST AI RMF for models and agents (with implementation steps) ↗
AI audit trails: What to log for models and agents, and how a Command Center captures it ↗
AI model catalog vs. AI model inventory: What's the difference (and where agents fit) ↗
AI transparency: What regulators, auditors, and users need to see from models and agents ↗
Bad data doesn't slow AI down. It scales the wrong answer. ↗
What makes an AI platform 'trusted'? 7 non-negotiables for governing models and agents ↗
AI needs context: Why LLMs still don’t understand real-world systems ↗
AWS and Collibra deepen partnership to bring business context and semantics to AWS SageMaker Catalog ↗
Data has gravity. Context does too. ↗
AI governance framework: A practical guide to governing AI at enterprise scale ↗
AI model governance: How to track, audit, and control AI models in production ↗
Compliance monitoring tools: What to look for when choosing a platform ↗
Continuous compliance monitoring: Moving from reactive audits to proactive control ↗
Data observability platform: How to proactively monitor and trust your data at scale ↗
Data observability platform: How to proactively monitor and trust your data at scale ↗
Metadata framework: Why your AI strategy needs a strong data foundation ↗
Metadata management: The missing layer that makes AI actually work ↗
What is a semantic layer? How shared business meaning powers better AI and analytics ↗
What is data democratization? How to give every team access to trusted, governed data ↗
Accelerating enterprise AI with high-trust outcomes ↗
AI governance and ethics: How to build responsible AI from the ground up ↗
Collibra named Databricks' 2026 Data Governance Partner of the Year ↗
Data as a product: How leading organizations are rethinking their data strategy ↗
Data product management: How to build a scalable, business-aligned data product strategy ↗
Data quality management: A framework for reliable, trusted and AI-ready data ↗
Enterprise AI governance: How to scale safe and compliant AI across the organization ↗
Enterprise risk management framework: Building a scalable foundation for regulatory compliance ↗
How to choose the right AI governance solution ↗
What are data products and why do they matter for AI, analytics and ROI? ↗
What is data lineage? How end-to-end traceability builds confidence in your data ↗
Solvency II compliance: What insurers need to know about data integrity and reporting ↗
Clinical data is only as credible as its context ↗
Trusted data, smarter AI: Unified governance for Snowflake ↗
The AI saddle point ↗
Clinical and operational data is as trustworthy as the processes behind it ↗
Compliance automation platform: From spreadsheet fire drills to automated control ↗
Data contracts 101: How to build trust between data producers and consumers ↗
Three years a Market Leader. In 2026, Collibra came out on top ↗
The hidden technical debt of AI: Why manual governance is slowing down your AI scale ↗
BCBS 239 explained: How banks can prove data integrity to regulators ↗
Enterprise data catalog: How to discover, understand, and trust your data assets ↗
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The end-to-end control plane for AI has arrived ↗
AI needs context: Why data alone is not enough ↗
Google Cloud and Collibra deepen their partnership to bring business context and semantics directly to the Knowledge Catalog ↗
Delivering AI at race pace without losing control ↗
The semantic layer has always been essential. Now it's existential. ↗
How the NIS2 Directive is redefining data intelligence and security ↗
Models are commodities, context is proprietary: Why context engineering is the new business standard ↗
AI Governance dashboard: Introducing catalog metrics for AI visibility ↗
AI trust score: Measure trust in every AI system ↗
Automated AI traceability across Vertex AI, SageMaker, Databricks ↗
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Bridge the data health gap between technical and business assets ↗
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Introducing Collibra Data Access: Connect the right users to the right data faster ↗
Meet the new Collibra Data Marketplace: A curated shopping experience for data products ↗
The new standard for metadata documentation: Meet your new AI writing assistant ↗
Unified AI registry: Your central inventory for AI use cases, models and agents ↗
Collibra AI: Turning AI innovation into everyday impact ↗
Accelerating data delivery using OSI with Snowflake and Collibra ↗
The bookends of AI: Why data and business impact still define success ↗
Your cloud data’s fingerprint: Discovering and curating for holistic visibility ↗
Four steps to truly democratize data access, safely ↗
Unlock data transparency with the new Collibra and Alteryx integration ↗
Before the algorithm: Why data profiling is the unsung hero of AI reliability ↗
Meet Janéa Wilkerson: Built to grow ↗
The AI connoisseur. Curating high-quality data for responsible innovation ↗
Collibra recognized as a Leader for the second consecutive year in the Gartner® Magic Quadrant™ for Data and Analytics Governance Platforms ↗
AI adoption has outrun data accountability ↗
The fastest path to trusted AI: Turning high-quality data into high-quality intelligence with SAP Business Data Cloud and Collibra ↗
Trusted agents at scale: Collibra launches MCP server in the Databricks Marketplace to power governed AI ↗
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The AI reckoning: Building ethical frameworks before the headlines hit ↗
The CIO’s mandate: Accelerating AI innovation without building a Tower of Babel ↗
The secret to trusted AI? It's your semantic layer ↗
Unified governance: The 'Invisible Infrastructure' powering tomorrow's data-driven enterprises ↗
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Collibra AI Governance and OSFI E-23: Navigating Canadian financial regulations ↗
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From innovation to accountability: Collibra Azure AI Foundry Integration helps enterprises govern AI agents and models at scale—without slowing delivery ↗
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New Collibra Survey by The Harris Poll Finds 84% of Decision Makers Say Organizations Must Increase AI Spending in 2026 to Remain Competitive with Big Tech, with Almost Half Saying AI is Falling Short ↗
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